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Vicarious AI raises another $50M
- dkural 9y agoWould be great if they showed some demonstrations / proof of any kind. DeepMind did great in that respect. I understand they're working on a different problem, but it's been a number of years; usually correct ideas don't take that long to show some promising progress.
- Barrin92 9y agoI'm honestly surprised how willing investors are to throw money at these ML startups that actually show barely any progress.
- qq66 9y ago"Show barely any progress" and "show barely any progress to the public" are very different. I don't have any inside information here, but a lack of public announcements is not proof of anything.
- arjo1 9y agoTheir 2017 paper: https://www.vicarious.com/img/icml2017-schemas.pdf https://www.vicarious.com/img/icml2017-schemas.pdf
- eli_gottlieb 9y agoThat's it? That tells me the same thing I saw when I attended a Vicarious researcher's talk at MIT CSAIL: they're basically reinventing stuff the Bayesian generative modelers in cognitive science have been doing for years, throwing some video-game playing at it, and calling it AI instead of cognitive science. Give me $50mil and I could do a good deal more than that, just because I bother to look stuff up!
- fuelfive 9y agoThere are a few papers up on the site already and some more coming. As a business, publications aren't really the KPIs we prioritize (vs an academic-style lab like DM or OAI).
- dkural 9y agoOut of curiosity, what's the KPI? p.s. I don't think papers qualify as a "demo". I'm with you re: not running it like an academic lab and chasing a minimal publishable unit or fashions of the time. Demo = Demonstrably do something with your technology no one could do before, ie beat people at Go in DeepMinds case, in your case you could set up your own benchmark / pass a Turing test for 3 year olds or something.
- congerous 9y agoKPI = amount of funds raised.
- lumost 9y agoThe economics for some of these labs is also pretty different from what you'd normally expect. There are numerous semi-private organizations in the defense space ( such as Boston Dynamics ) and similarly in the pharmaceutical space. Which may only produce commercially viable technology after a decade or more. For many of these entities, the funding dynamics are dependent on the overall scope of the problem along with the quality of the team rather than any direct foreseeable economic outcome.
- dkural 9y agoI understand, I don't mean commercial progress either.
- jonmc12 9y agoInteresting the bird analogy again - “airplanes don’t flap their wings” was in a recent article by Jeff Hawkins describing Numenta's approach (http://spectrum.ieee.org/computing/software/what-intelligent-machines-need-to-learn-from-the-neocortex http://spectrum.ieee.org/computing/software/what-intelligent...). Vicarious co-founder Dileep George was also a co-founder at Numenta. Perhaps they have similar philosophies to approach but Numenta modeling the Neo-cortex while Vicarious modeling the entire brain?
- boltzmannbrain 9y agoNo, quite different approaches and goals.
- teabee89 9y agoThey agree on the bird analogy, except Numenta (IMHO rightfully) thinks you can't come up with airplane designs without having understood how birds actually fly.
- arketyp 9y agoBack in the Dileep George days Numenta sought mathematical support for their theory in a Bayesian approach à la Judea Pearl. But I don't think they ever had any illusions that the brain explicitly performs statistical calculations. Hawkins et al. at Numenta are now embracing the theory of sparse distributed representation, developing upon the work of Pentti Kanerva as a formal foundation. It's biologically much more plausible, but technologically less feasible (with the current hardware paradigm). I suspect Dileep George in the end was more eager to put the theory into use.
- skummetmaelk 9y agoAirplanes don't flap their their wings, but they are also orders of magnitude less energy efficient than birds. If you want computational power on the scale of the brain, power consumption is a real concern.
- Houshalter 9y agoAre planes less energy efficient than birds? Sure they consume more energy, but they can lift many orders of magnitude more weight. To carry that much weight, that much distance, you would need an unfathomable number of birds. Flying for a very long time. The same with with brains. As far as I can tell, transistors are orders of magnitude more energy efficient than synapses. Synapses use tons of slow chemical reactions to send a signal. Transistors just send a few electrons near light speed.
- free2rhyme214 9y agoOpenAI & DeepMind > Vicarious
- Hyperbolic 9y agoI am always skeptical of people trying to "emulate" the human brain in machine learning. We currently do not have the tools to accurately record and analyze the dynamics of networks of neurons in the brain, and any group that claims to advance ML with knowledge of the cortex is spouting bullshit. Modern advances in ML are driven by great engineering, not biological insight.
- shahbaby 9y agoEven DeepMind says that future advances will come from neuroscience. https://www.theverge.com/2017/7/19/15998610/ai-neuroscience-machine-learning-deepmind-demis-hassabis-interview https://www.theverge.com/2017/7/19/15998610/ai-neuroscience-... In the field of AI, our "great engineering" is not even a worthy comparison to what nature has achieved. Maybe there are a few more things to learn from it. Also we've been studying the neocortex for a long time and have learned a lot more about it than most people realize.
- ogrisel 9y agoWhile Demis Hassabis and probably some DeepMind researchers use some understandings from the neuroscience literature as an inspiration for their work, I am pretty sure that a majority of DeepMind researchers would rather use a combination of mathematics and trial and error experiments to build an intuition to guide the design of their next iteration of intelligent learning systems.
- ogrisel 9y agoTo be more factual: a majority of papers published by researchers at DeepMind do not cite any result from the neuroscience literature in their bibliography. Instead they cite other papers from the Machine Learning community.
- shahbaby 9y agoThe point is that when mainstream ML begins to realize that there are limitations to the current cartoonish representations of neural networks, they then go back to the biology to see what they're missing. However there are other companies, like Numenta, which realized decades ago that the current techniques will not be sufficient for general intelligence. Numenta is not trying to emulate the brain like the Human Brain Project, they are aiming to learn the principles behind the neocortex and replicate it in software. Again, I don't think most people know enough about the neocortex because if they did, we probably wouldn't be so quick to discard the only real example of intelligence we have.
- rf15 9y agoDid somebody say "Rocket AI"?
- blueyes 9y agoNever before has an AI startup done so little with so much. That puts their total funding with debt at around $130 million. It's an utter waste. Reminds me of the $15 billion IBM has spent on Watson. The people with the money are very poor judges of technologists in this space.
- jorgemf 9y agoCan you expand what have Vicarious done?
- jgalt212 9y agogiven his answer the implication is zero, but I too an curious about any of their accomplishments, proofs of concepts and/or MVPs.
- blueyes 9y agoThey're secretive about it, a bit like Watson. If they could really beat the benchmarks, they probably would have let us know by now.
- blueyes 9y agoThey've published a few research papers. Few other researchers cite them, so it's hard to argue that their research has been influential, or even significant. In 2013 they announced they had solved/broken CAPTCHA, but refused to share their code, for which they were criticized: https://www.vicarious.com/news-detail-02.html https://www.vicarious.com/news-detail-02.html More recently, they published a paper on what they call Schema Networks, which are an attempt to blend deep learning with concepts. They're winning Atari games with that, but DeepMind did it years ago. https://arxiv.org/abs/1706.04317 https://arxiv.org/abs/1706.04317 They're seven years old, and until recently, they'd raised $70-$80 million. I would have expected more than a few research papers in that time, if I were their investors.
- jorgemf 9y ago